Soil Salinity Detection Using Salinity Indices from Landsat 8 Satellite Image at Rampal, Bangladesh

被引:0
|
作者
Hassan R. [1 ]
Ahmed Z. [1 ]
Islam M.T. [1 ]
Alam R. [1 ]
Xie Z. [2 ]
机构
[1] Department of Geography and Environment, Shahjalal University of Science and Technology, Sylhet
[2] Department of Geosciences, Florida Atlantic University, Boca Raton, FL
关键词
Landsat; 8; Rampal; Salinity indices; Soil salinity;
D O I
10.1007/s41976-020-00041-y
中图分类号
学科分类号
摘要
Soil salinization has now become a hazardous threat to the environment in context to climate change. The low-lying southwest region of Bangladesh has a high level of salinity in water and soil that is expected to aggravate consequently with the increase in sea level rise. This dominance of salty water has been reported being more intensive since the past couple of decades. As the southwestern region is much dependent on agriculture, the intrusion of soil salinity has been adversely impacting the economy as well as playing a constraint role for planning and restoring soil fertility. The evaluation of soil salinity is critical for protection, planning, and restoring soil fertility as the economy of the southwestern region is mostly dependent on agriculture. This study attempts to determine the soil salinity in Rampal Upazila, Bagerhat, utilizing Landsat 8 OLI satellite imageries with derived salinity indices and band combinations. Salinity indices were derived from different band calculations. Besides, statistical analysis between soil salinity, electrical conductivity (EC, dS/m), and salinity indices has been applied which implies that spectral reflectance has a significant correlation with soil salinity where VSSI had the highest correlation coefficient of 0.865. The estimated soil salinity from regression analysis reveals an acceptable level of significance and having a minimum standard error of estimate of 1.082 between EC and spectral values. The Z-score comparison between the bands and indices also implies that the VSSI had the highest correlation factor. The findings of this study will be useful for agriculture, land use, land management, and planning to reduce both social and economic loss by considering the spatial distribution of salinity on a large scale. Mitigation measures should be taken by the respected authorities immediately; otherwise, this saline situation of Rampal Upazila will be getting worse. However, the approach of using remote sensing technology may not be as accurate as ground-based assessment; it can be an influential evidence if spatiotemporal monitoring can be conducted constantly further. Underdeveloped and also developing countries could get benefited using this low-cost technique for detecting the soil salinity. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG part of Springer Nature.
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页码:1 / 12
页数:11
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